opencv在手机上实现照片背景虚化
概述
使用androidstudio开发,在手机上实现照片背景虚化
详细
一、准备工作
1、需要下载安装androidstudio和相关JDK,这两者下载安装和普通软件一样,
JDK:
http://www.oracle.com/technetwork/java/javase/downloads/index.html
androidstuido:
http://www.android-studio.org/
2、本例子在安卓手机上开发图像美化效果,用以在手机相机上实现类似高羰数码相机的背景虚化特效
3.软件下载安装配置完成后,下载本实例解压,打开androidstudio,选择FILE-》OPEN菜单,在弹出的对话中选择实例解压的位置,打开就行了
二、程序实现
1、主程序包含一个源码主文件MainActivity一个布局文件layout及相当菜单资源
2、实现思路怎样
要使用软件技术精确的背景虚化,需要经过三个步骤:
一是选定区域,根据远区使用抠图技术实现前背景分离
二对背景根据需要使用高斯或者平均值等模糊方法处理
三把处理后的背景和前景合并
3、具体设计到哪些代码
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 | import android.app.Activity; import android.app.ProgressDialog; import android.content.Intent; import android.database.Cursor; import android.graphics.Bitmap; import android.graphics.BitmapFactory; import android.graphics.Canvas; import android.graphics.Paint; import android.graphics.RectF; import android.graphics.drawable.BitmapDrawable; import android.net.Uri; import android.os.AsyncTask; import android.os.Bundle; import android.provider.MediaStore; import android.util.Log; import android.view.Menu; import android.view.MenuItem; import android.view.MotionEvent; import android.view.View; import android.widget.ImageView; import org.opencv.android.BaseLoaderCallback; import org.opencv.android.LoaderCallbackInterface; import org.opencv.android.OpenCVLoader; import org.opencv.core.Core; import org.opencv.core.CvType; import org.opencv.core.Mat; import org.opencv.core.Point; import org.opencv.core.Rect; import org.opencv.core.Scalar; import org.opencv.core.Size; import org.opencv.imgcodecs.Imgcodecs; import org.opencv.imgproc.Imgproc; public class MainActivity extends Activity { static final int REQUEST_OPEN_IMAGE = 1 ; String mCurrentPhotoPath; Bitmap mBitmap; ImageView mImageView; int touchCount = 0 ; Point tl; Point br; boolean targetChose = false ; ProgressDialog dlg; private BaseLoaderCallback mLoaderCallback = new BaseLoaderCallback( this ) { @Override public void onManagerConnected( int status) { switch (status) { case LoaderCallbackInterface.SUCCESS: { //Log.i(TAG, "OpenCV loaded successfully"); } break ; default : { super .onManagerConnected(status); } break ; } } }; @Override public void onResume() { super .onResume(); if (!OpenCVLoader.initDebug()) { Log.d( "OpenCV" , "Internal OpenCV library not found. Using OpenCV Manager for initialization" ); OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_3_0_0, this , mLoaderCallback); } else { Log.d( "OpenCV" , "OpenCV library found inside package. Using it!" ); mLoaderCallback.onManagerConnected(LoaderCallbackInterface.SUCCESS); } } @Override protected void onCreate(Bundle savedInstanceState) { super .onCreate(savedInstanceState); setContentView(R.layout.activity_main); mImageView = (ImageView) findViewById(R.id.imgDisplay); dlg = new ProgressDialog( this ); tl = new Point(); br = new Point(); // if (!OpenCVLoader.initDebug()) { // Handle initialization error //} } @Override public boolean onCreateOptionsMenu(Menu menu) { // Inflate the menu; this adds items to the action bar if it is present. getMenuInflater().inflate(R.menu.menu_main, menu); return true ; } int scaleFactor = 1 ; private void setPic() { int targetW = 720 ; //mImageView.getWidth(); int targetH = 1128 ; //mImageView.getHeight(); Log.i( ">>>>>" , "targetW=" +targetW); Log.i( ">>>>>" , "targetH=" + targetH); BitmapFactory.Options bmOptions = new BitmapFactory.Options(); bmOptions.inJustDecodeBounds = true ; BitmapFactory.decodeFile(mCurrentPhotoPath, bmOptions); int photoW = bmOptions.outWidth; int photoH = bmOptions.outHeight; Log.i( ">>>>>" , "photoW=" +photoW); Log.i( ">>>>>" , "photoH=" + photoH); scaleFactor = Math.max(photoW / targetW, photoH / targetH)+ 1 ; Log.i( ">>>>>" , "photoW / targetW=" +(photoW / targetW)); Log.i( ">>>>>" , "photoH / targetH=" +(photoH / targetH)); bmOptions.inJustDecodeBounds = false ; bmOptions.inSampleSize = scaleFactor; bmOptions.inPurgeable = true ; mBitmap = BitmapFactory.decodeFile(mCurrentPhotoPath, bmOptions); mImageView.setImageBitmap(mBitmap); Log.i( ">>>>>" , "mBitmap.getWidth()=" +mBitmap.getWidth()); Log.i( ">>>>>" , "mBitmap.getHeight()=" + mBitmap.getHeight()); } @Override protected void onActivityResult( int requestCode, int resultCode, Intent data) { switch (requestCode) { case REQUEST_OPEN_IMAGE: if (resultCode == RESULT_OK) { Uri imgUri = data.getData(); String[] filePathColumn = { MediaStore.Images.Media.DATA }; Cursor cursor = getContentResolver().query(imgUri, filePathColumn, null , null , null ); cursor.moveToFirst(); int colIndex = cursor.getColumnIndex(filePathColumn[ 0 ]); mCurrentPhotoPath = cursor.getString(colIndex); cursor.close(); setPic(); } break ; } } @Override public boolean onOptionsItemSelected(MenuItem item) { int id = item.getItemId(); switch (id) { case R.id.action_open_img: Intent getPictureIntent = new Intent(Intent.ACTION_GET_CONTENT); getPictureIntent.setType( "image/*" ); Intent pickPictureIntent = new Intent(Intent.ACTION_PICK, MediaStore.Images.Media.EXTERNAL_CONTENT_URI); Intent chooserIntent = Intent.createChooser(getPictureIntent, "Select Image" ); chooserIntent.putExtra(Intent.EXTRA_INITIAL_INTENTS, new Intent[] { pickPictureIntent }); startActivityForResult(chooserIntent, REQUEST_OPEN_IMAGE); return true ; case R.id.action_choose_target: if (mCurrentPhotoPath != null ) targetChose = false ; mImageView.setOnTouchListener( new View.OnTouchListener() { @Override public boolean onTouch(View v, MotionEvent event) { int cx = (mImageView.getWidth()-mBitmap.getWidth())/ 2 ; int cy = (mImageView.getHeight()-mBitmap.getHeight())/ 2 ; if (event.getAction() == MotionEvent.ACTION_DOWN) { if (touchCount == 0 ) { tl.x = event.getX(); //300;// tl.y = event.getY(); //300;// touchCount++; } else if (touchCount == 1 ) { br.x = event.getX(); //1100;// br.y = event.getY(); //1200;// Paint rectPaint = new Paint(); rectPaint.setARGB( 255 , 255 , 0 , 0 ); rectPaint.setStyle(Paint.Style.STROKE); rectPaint.setStrokeWidth( 3 ); Bitmap tmpBm = Bitmap.createBitmap(mBitmap.getWidth(), mBitmap.getHeight(), Bitmap.Config.RGB_565); Canvas tmpCanvas = new Canvas(tmpBm); tmpCanvas.drawBitmap(mBitmap, 0 , 0 , null ); tmpCanvas.drawRect( new RectF(( float ) tl.x, ( float ) tl.y, ( float ) br.x, ( float ) br.y), rectPaint); mImageView.setImageDrawable( new BitmapDrawable(getResources(), tmpBm)); targetChose = true ; touchCount = 0 ; mImageView.setOnTouchListener( null ); } } return true ; } }); return true ; case R.id.action_cut_image: if (mCurrentPhotoPath != null && targetChose) { new ProcessImageTask().execute(); targetChose = false ; } return true ; } return super .onOptionsItemSelected(item); } private class ProcessImageTask extends AsyncTask<Integer, Integer, Integer> { Mat img; Mat foreground; @Override protected void onPreExecute() { super .onPreExecute(); dlg.setMessage( "Processing Image..." ); dlg.setCancelable( false ); dlg.setIndeterminate( true ); dlg.show(); } @Override protected Integer doInBackground(Integer... params) { //Mat img = new Mat(mBitmap.getHeight(), mBitmap.getHeight(), CvType.CV_8UC3); //Utils.bitmapToMat(mBitmap, img); long ll = System.currentTimeMillis(); Log.i( ">>>>>" , "start=" +ll); img = Imgcodecs.imread(mCurrentPhotoPath); Imgproc.resize(img, img, new Size(img.cols()/scaleFactor, img.rows()/scaleFactor)); Log.i( ">>>>>" , "11111=" + System.currentTimeMillis()+ "@@@@@" +(System.currentTimeMillis()-ll)); Mat background = new Mat(img.size(), CvType.CV_8UC3, new Scalar( 255 , 255 , 255 )); Mat firstMask = new Mat(); Mat bgModel = new Mat(); Mat fgModel = new Mat(); Mat mask; Mat source = new Mat( 1 , 1 , CvType.CV_8U, new Scalar(Imgproc.GC_PR_FGD)); Mat dst = new Mat(); Rect rect = new Rect(tl, br); Log.i( ">>>>>" , "22222=" +System.currentTimeMillis()+ "@@@@@" +(System.currentTimeMillis()-ll)); Imgproc.grabCut(img, firstMask, rect, bgModel, fgModel, 1 , Imgproc.GC_INIT_WITH_RECT); Log.i( ">>>>>" , "33333=" + System.currentTimeMillis() + "@@@@@" + (System.currentTimeMillis() - ll)); Core.compare(firstMask, source, firstMask, Core.CMP_EQ); Log.i( ">>>>>" , "44444=" + System.currentTimeMillis() + "@@@@@" + (System.currentTimeMillis() - ll)); foreground = new Mat(img.size(), CvType.CV_8UC3, new Scalar( 255 , 255 , 255 )); ///// img.copyTo(foreground); Imgproc.blur(foreground, foreground, new Size( 20 , 20 )); Log.i( ">>>>>" , "55555=" + System.currentTimeMillis()+ "@@@@@" +(System.currentTimeMillis()-ll)); ///// img.copyTo(foreground, firstMask); Log.i( ">>>>>" , "66666=" + System.currentTimeMillis()+ "@@@@@" +(System.currentTimeMillis()-ll)); firstMask.release(); source.release(); bgModel.release(); fgModel.release(); Imgcodecs.imwrite(mCurrentPhotoPath + ".png" , foreground); return 0 ; } @Override protected void onPostExecute(Integer result) { super .onPostExecute(result); Bitmap jpg = BitmapFactory .decodeFile(mCurrentPhotoPath + ".png" ); mImageView.setScaleType(ImageView.ScaleType.CENTER_INSIDE); mImageView.setAdjustViewBounds( true ); mImageView.setPadding( 2 , 2 , 2 , 2 ); mImageView.setImageBitmap(jpg); mImageView.invalidate(); dlg.dismiss(); } } } |
4、配置文件说明
三、运行效果
运行,右键项目:Run as -》Android Application1、运行时的截图
四、其他补充
1、Imgproc.grab分割前景效果比较好,但速度比较慢,如果是确认是固定的比如人脸,水果,植物,可以使用其他OPENCV提代的其他分割方法以加快速度
2.有关模糊,可以根据需要选择合适的模糊算法,比如高斯,比如运动模糊等
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